479
ISSN 1061-9348, Journal of Analytical Chemistry, 2020, Vol. 75, No. 4, pp. 479–486. © Pleiades Publishing, Ltd., 2020.
Rapid Determination of Total Phenol in Leaf Extracts of a Medicinal
Plant Using Infrared Spectroscopy and Chemometric Methods
Lestyo Wulandari
a,
*, Nia Kristiningrum
a
, and Fracilia Arinda Ratnasari
a
a
Faculty of Pharmacy, University of Jember, 68121 Indonesia
*e-mail: lestyowulandari@unej.ac.id
Received October 11, 2017; revised February 2, 2018; accepted October 26, 2019
Abstract—Infrared spectroscopy combined with chemometrics has been applied for simple and rapid deter-
mination of total phenol in leaf extracts of medicinal plants. Phenols were extracted from leaves of medicinal
plants by ultrasonication and maceration methods. Fourier transform infrared and near infrared spectra of
selected leaf extracts of medicinal plants were correlated with total phenolic content using chemometrics. The
chemometric methods used for calibration analysis were partial least square (PLS), principal component
regression, and support vector machines regression and for classification analysis linear discriminant analysis
(LDA), soft independent modelling of class analogies, and support vector machines classification were
applied. The results have shown that the PLS method gives the best calibration model with the coefficient of
determination (R
2
) of 0.9920, whereas the root mean square error of calibration is 2.0049. In addition, R
2
of
leave-one-out cross validation and 2-fold-cross-validation were 0.9939 and 0.9834, respectively. Linear dis-
criminant analysis showed good results of classification analysis with 100% accuracy. The PLS and LDA
models were then applicated to real samples. The paired samples t-test showed that total phenol content mea-
sured by NIR and UV-Vis spectroscopy methods gave no significant differences (p > 0.05).
Keywords: total phenol, infrared spectroscopy, chemometrics
DOI: 10.1134/S1061934820040176
Indonesia is an archipelago country that has abun-
dant and diverse flora and fauna. The islands are
occupied with 40000 recorded plant species in which
6000 species have been claimed to have medicinal
properties. Medicinal plants have been used through
generations by the indigenous people of Indonesia [1].
The medicinal plant constituents responsible for tradi-
tional medicinal claims of the plant are called bioac-
tive secondary metabolites. Isolation procedures pro-
duce pure bioactive secondary metabolites in which
final pharmacological test confirmes the use of
medicinal plants [2].
One of highly and widely distributed groups of bio-
active secondary metabolites are phenols. Phenolic
molecules have one or more hydroxyl groups attached
to an aromatic ring. which is in the plant, the mole-
cules is synthesized in the chloroplasts. These mole-
cules are deposited in cell vacuole which is used to
strengthen the secondary cell wall structure [3]. Phe-
nolic compounds are widely used as antioxidants to
prevent heart diseases, reduce inflammation, decrease
the risk of cancer and diabetes [4].
Several analytical techniques have been developed
for determining total phenol concentration, such as
UV-Vis spectroscopy, thin layer chromatography,
paper chromatography, gas chromatography, and
HPLC. However, these methods are time and effort
consuming [4, 5]. Therefore, there is a need for the
development of rapid and reliable analytical tech-
niques.
Infrared spectroscopy is an effective option due to
a fast, non-polluting, and non-destructive analysis as
well as a small consumption of chemical reagents.
Near infrared (NIR) spectroscopy is widely used in
pharmaceutical analysis of raw materials, process
monitoring, and quality control [6]. Near infrared
spectroscopy also shows promising ability for discrim-
ination of similar biological materials, such as pea [7],
fruits [8], wine [9]. Some papers have been published
regarding the use of infrared spectroscopy for the
quantitation of active compounds in herbal products
[10, 11]. Although infrared spectroscopy has become
important in analysis of pharmaceutical samples
because of the ruggedness, infrared spectroscopy
spectra are very complicated and difficult to interpret.
Therefore, multivariate statistical methods are
required [12, 13].
Multivariate statistical methods are able to extract
required information from the spectral data for both
qualitative and quantitative determination in which
the technique is referred to as a chemometric method
[14]. This paper reported the development of infrared
spectroscopy combined with chemometric methods
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